Compared with computers, the human brain is incredibly energy efficient. Scientists are therefore drawing on how the brain and its interconnected neurons function for inspiration in designing innovative computing technologies. They foresee that these brain-​inspired computing systems, will be more energy efficient than conventional ones, as well as better at performing machine-​learning tasks.

Using an artificial intelligence (AI) tool that emulates how humans visualize and is trained to recognize and classify images, investigators constructed a model that predicts the postoperative recurrence of Crohn disease with high accuracy by evaluating histological images. The AI tool also revealed previously unrecognized differences in adipose cells and significant differences in the extent of mast cell infiltration in the subserosa, or outer lining of the intestine, comparing patients with and without disease recurrence.

A text messaging program successfully supported, informed and motivated people after a heart attack on how to prevent a second heart attack, according to new research published today in the American Heart Association’s flagship, peer-reviewed journal Circulation. Study participants showed minor improvements in healthy lifestyle measures after 12 months, although participants had no improvements in taking medications as prescribed.

Researchers at the University of Missouri are applying a form of artificial intelligence (AI) - previously used to analyze how National Basketball Association (NBA) players move their bodies - to now help scientists develop new drug therapies for medical treatments targeting cancers and other diseases.

Atrial fibrillation, the most common cardiac rhythm abnormality, has been linked to one-third of ischemic strokes, the most common type of stroke. But atrial fibrillation is underdiagnosed, partly because many patients are asymptomatic.

Artificial intelligence-enabled electrocardiography (ECG) was recently shown to identify the presence of brief episodes of atrial fibrillation, and the ability of an AI-enabled ECG algorithm to predict atrial fibrillation up to 10 years before clinical diagnosis has been confirmed in a population-based study conducted by Mayo Clinic researchers.

An artificial intelligence (AI) tool developed by Cedars-Sinai investigators accurately predicted who would develop pancreatic cancer based on what their CT scan images looked like years prior to being diagnosed with the disease. The findings, which may help prevent death through early detection of one of the most challenging cancers to treat, are published in the journal Cancer Biomarkers.

26 - 28 April 2022, Berlin, Germany.
What plans does the new federal government have concerning the digital transformation of the healthcare sector? What are the initial experiences of doctors regarding ePrescriptions? What can we learn from Israel in respect of digital health and the use of AI? These are just some of the questions that DMEA - Connecting Digital Health will be asking from 26 to 28 April. For two years Europe's leading health IT event took place in an entirely virtual format.